{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T21:21:35Z","timestamp":1773955295334,"version":"3.50.1"},"reference-count":14,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2018,10,14]],"date-time":"2018-10-14T00:00:00Z","timestamp":1539475200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The presence of border noise in Sentinel-1 Ground Range Detected (GRD) products is an undesired processing artifact that limits their full exploitation in a number of applications. All of the Sentinel-1 GRD products generated before March 2018\u2014more than 800,000\u2014are affected by this particular type of noise. In March 2018, an official fix was deployed that solved the problem for a large portion of the newly generated products, but it did not cover the entire range of products, hence the need for an operational tool that is able to effectively and consistently remove border noise in an automated way. Currently, a few solutions have been proposed that try to address the problem, but all of them have limitations. The scope of this paper is therefore to present a new method based on mathematical morphology for the automatic detection and masking of border noise in Sentinel-1 GRD products that is able to overcome the existing limitations. To evaluate the performance of the method, a detailed numerical assessment was carried out, using, as a benchmark, the \u2018Remove GRD Border Noise\u2019 module integrated in ESA\u2019s Sentinel Application Platform. The results showed that the proposed method is capable of very accurately removing the undesired noisy pixels from GRD images, regardless of their acquisition mode, polarization, or resolution and can cope with challenging features within the image scenes that typically affect other approaches.<\/jats:p>","DOI":"10.3390\/s18103454","type":"journal-article","created":{"date-parts":[[2018,10,15]],"date-time":"2018-10-15T03:43:01Z","timestamp":1539574981000},"page":"3454","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["An Operational Tool for the Automatic Detection and Removal of Border Noise in Sentinel-1 GRD Products"],"prefix":"10.3390","volume":"18","author":[{"given":"Mattia","family":"Stasolla","sequence":"first","affiliation":[{"name":"Signal &amp; Image Center, Royal Military Academy, B\u20131000 Brussels, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8992-3877","authenticated-orcid":false,"given":"Xavier","family":"Neyt","sequence":"additional","affiliation":[{"name":"Signal &amp; Image Center, Royal Military Academy, B\u20131000 Brussels, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,10,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.rse.2011.05.028","article-title":"GMES Sentinel-1 mission","volume":"120","author":"Torres","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_2","unstructured":"Aulard-Macler, M. (2011). Sentinel-1 Product Definition, MacDonald, Dettwiler and Associates. Document Reference MPC-0240."},{"key":"ref_3","unstructured":"Bourbigot, M. (2018). Release Note of S-1 IPF for End Users of Sentinel-1 Products, European Space Agency. Document Reference MPC-0389, Collecte Localisation Satellites."},{"key":"ref_4","unstructured":"Hajduch, G. (2018). Masking \u201cNo-Value\u201d Pixels on GRD Products Generated by the Sentinel-1 ESA IPF, European Space Agency. Document Reference MPC-0243, Collecte Localisation Satellites."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"777","DOI":"10.1109\/JSTARS.2017.2787650","article-title":"Methods to Remove the Border Noise From Sentinel-1 Synthetic Aperture Radar Data: Implications and Importance For Time-Series Analysis","volume":"11","author":"Ali","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. 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Sentinel-1 Data Border Noise Removal and Seamless Synthetic Aperture Radar Mosaic Generation. Proceedings, 2.","DOI":"10.3390\/ecrs-2-05143"},{"key":"ref_10","unstructured":"Zuhlke, M., Fomferra, N., Brockmann, C., Peters, M., Veci, L., Malik, J., and Regner, P. (2015, January 2\u20135). SNAP (Sentinel Application Platform) and the ESA Sentinel 3 Toolbox. Proceedings of the Sentinel-3 for Science Workshop, Venice, Italy."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2990","DOI":"10.1080\/01431161.2016.1192304","article-title":"Sentinel-1-based flood mapping: A fully automated processing chain","volume":"37","author":"Twele","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Dyatmika, H.S., Sambodo, K.A., and Budiono, M.E. (2017). Noise Removal Using Thresholding and Segmentation for Random Noise Sentinel-1 Data, IOP Publishing.","DOI":"10.1088\/1755-1315\/54\/1\/012105"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Soille, P. (2004). Morphological Image Analysis: Principles and Applications, Springer.","DOI":"10.1007\/978-3-662-05088-0"},{"key":"ref_14","unstructured":"Gonzalez, R.C., and Woods, R.E. (2002). Digital Image Processing, Prentice Hall. [2nd ed.]."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/10\/3454\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:25:34Z","timestamp":1760196334000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/18\/10\/3454"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,14]]},"references-count":14,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2018,10]]}},"alternative-id":["s18103454"],"URL":"https:\/\/doi.org\/10.3390\/s18103454","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,10,14]]}}}